Papers
2
Total Citations
9
H-Index
2
About
Jyh‐Cheng Yu is a robotics researcher whose work centers on autonomous mobile systems, multi-sensor fusion, and intelligent navigation. His research addresses practical limitations in consumer robotics, particularly in the domain of autonomous lawn mowing — a field where conventional solutions rely on costly buried wire installations and inefficient random-walk algorithms. Yu's contributions focus on replacing these outdated approaches with sophisticated sensor fusion architectures that integrate inertial measurement units, wheel encoders, LiDAR, and RGB-D cameras to enable robust Simultaneous Localization and Mapping (SLAM) and automated boundary detection through image recognition. His 2022 study on multi-sensor fusion-based SLAM for robotic lawn mowers has garnered 7 citations, demonstrating growing interest from the robotics community in his methodology. A companion paper on autonomous boundary detection using image recognition has further extended his framework, offering a vision-driven alternative to physical wire demarcation. Together, these works represent a meaningful step toward fully autonomous, installation-free outdoor robotics. Yu's research appeals to scholars working at the intersection of computer vision, mobile robotics, and practical automation, positioning him as an emerging contributor to intelligent field robotics and autonomous systems engineering.
Research Focus
Key Achievements
Top Papers
- 1
- 2